Comprehensive Analysis of the Mechanism of Periodontitis-Related mRNA Expression Combined with Upstream Methylation and ceRNA Regulation.

Abstract

Background: Periodontitis is a multifactorial disease mainly caused by the formation of plaque biofilm, which can lead to the gradual destruction of tooth-supporting tissues. Current research on the genetics and epigenetics of periodontitis remains relatively limited, and the molecular mechanisms remain largely unknown. Objective: Our aims were to construct competitive endogenous RNA (ceRNA) network and determine DNA methylation patterns of target genes to help elucidate the pathogenesis of periodontitis. Methods: We analyzed the expression profiles of the GSE16134, GSE54710, GSE10334, and GSE59932 datasets from the Gene Expression Omnibus database through the weighted gene coexpression network analysis system and screened mRNAs that are regulated by the level of methylation and are associated with the occurrence of periodontitis. Next, a lncRNA-miRNA-mRNA ceRNA network was constructed using databases including miRanda and TargetScan. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were conducted for genes in the clinically significant modules. Finally, a protein-protein interaction network was built. Results: We finally identified four mRNAs, four miRNAs, and six lncRNAs as shared differentially expressed genes related to the periodontitis inflammation pathway. IL-6, IFNA17, CXCL12, and TNFRSF13C were identified as key genes whose expression was significantly enriched in the nuclear factor κB and TLR4 pathways. Moreover, the expression of 28 genes were downregulated by hypermethylation and 70 genes were upregulated by hypomethylation. Conclusions: The constructed ceRNA network can improve our understanding of the pathogenesis of periodontitis. Candidate mRNAs from the ceRNA network could serve as new therapeutic targets and prognostic biomarkers in periodontitis.